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It is well established that El Niño–Southern Oscillation (ENSO) impacts the North Atlantic–European (NAE) climate, with the strongest influence in winter. In late winter, the ENSO signal travels via both tropospheric and stratospheric pathways to the NAE sector and often projects onto the North Atlantic Oscillation. However, this signal does not strengthen gradually during winter, and some studies have suggested that the ENSO signal is different between early and late winter and that the teleconnections involved in the early winter subperiod are not well understood. In this study, we investigate the ENSO teleconnection to NAE in early winter (November–December) and characterize the possible mechanisms involved in that teleconnection. To do so, observations, reanalysis data and the output of different types of model simulations have been used. We show that the intraseasonal winter shift of the NAE response to ENSO is detected for both El Niño and La Niña and is significant in both observations and initialized predictions, but it is not reproduced by free-running Coupled Model Intercomparison Project phase 5 (CMIP5) models. The teleconnection is established through the troposphere in early winter and is related to ENSO effects over the Gulf of Mexico and Caribbean Sea that appear in rainfall and reach the NAE region. CMIP5 model biases in equatorial Pacific ENSO sea surface temperature patterns and strength appear to explain the lack of signal in the Gulf of Mexico and Caribbean Sea and, hence, their inability to reproduce the intraseasonal shift of the ENSO signal over Europe.

Skilful predictions of near-term climate extremes are key to a resilient society. However, standard methods of analysing seasonal forecasts are not optimised to identify the rarer and most impactful extremes. For example, standard tercile probability maps, used in real-time regional climate outlooks, failed to convey the extreme magnitude of summer 2022 Pakistan rainfall that was, in fact, widely predicted by seasonal forecasts. Here we argue that, in this case, a strong summer La Niña provided a window of opportunity to issue a much more confident forecast for extreme rainfall than average skill estimates would suggest. We explore ways of building forecast confidence via a physical understanding of dynamical mechanisms, perturbation experiments to isolate extreme drivers, and simple empirical relationships. We highlight the need for more detailed routine monitoring of forecasts, with improved tools, to identify regional climate extremes and hence utilise windows of opportunity to issue trustworthy and actionable early warnings. This paper highlights the potential for improved monitoring and physical understanding to identify windows of opportunity for more confident seasonal forecasts and early warnings of regional climate extremes, such as the Pakistan floods of 2022.

Summer climate in the North Atlantic–European sector possesses a principal pattern of year-to-year variability that is the parallel to the well-known North Atlantic Oscillation in winter. This summer North Atlantic Oscillation (SNAO) is defined here as the first empirical orthogonal function (EOF) of observed summertime extratropical North Atlantic pressure at mean sea level. It is shown to be characterized by a more northerly location and smaller spatial scale than its winter counterpart. The SNAO is also detected by cluster analysis and has a near-equivalent barotropic structure on daily and monthly time scales. Although of lesser amplitude than its wintertime counterpart, the SNAO exerts a strong influence on northern European rainfall, temperature, and cloudiness through changes in the position of the North Atlantic storm track. It is, therefore, of key importance in generating summer climate extremes, including flooding, drought, and heat stress in northwestern Europe. The El Niño–Southern Oscillation (ENSO) phenomenon is known to influence summertime European climate; however, interannual variations of the SNAO are only weakly influenced by ENSO. On interdecadal time scales, both modeling and observational results indicate that SNAO variations are partly related to the Atlantic multidecadal oscillation. It is shown that SNAO variations extend far back in time, as evidenced by reconstructions of SNAO variations back to 1706 using tree-ring records. Very long instrumental records, such as central England temperature, are used to validate the reconstruction. Finally, two climate models are shown to simulate the present-day SNAO and predict a trend toward a more positive index phase in the future under increasing greenhouse gas concentrations. This implies the long-term likelihood of increased summer drought for northwestern Europe.

A new climate model, HadGEM3 N96ORCA1, is presented that is part of the GC3.1 configuration of HadGEM3. N96ORCA1 has a horizontal resolution of ~135 km in the atmosphere and 1° in the ocean and requires an order of magnitude less computing power than its medium‐resolution counterpart, N216ORCA025, while retaining a high degree of performance traceability. Scientific performance is compared to both observations and the N216ORCA025 model. N96ORCA1 reproduces observed climate mean and variability almost as well as N216ORCA025. Patterns of biases are similar across the two models. In the northwest Atlantic, N96ORCA1 shows a cold surface bias of up to 6 K, typical of ocean models of this resolution. The strength of the Atlantic meridional overturning circulation (16 to 17 Sv) matches observations. In the Southern Ocean, a warm surface bias (up to 2 K) is smaller than in N216ORCA025 and linked to improved ocean circulation. Model El Niño/Southern Oscillation and Atlantic Multidecadal Variability are close to observations. Both the cold bias in the Northern Hemisphere (N96ORCA1) and the warm bias in the Southern Hemisphere (N216ORCA025) develop in the first few decades of the simulations. As in many comparable climate models, simulated interhemispheric gradients of top‐of‐atmosphere radiation are larger than observations suggest, with contributions from both hemispheres. HadGEM3 GC3.1 N96ORCA1 constitutes the physical core of the UK Earth System Model (UKESM1) and will be used extensively in the Coupled Model Intercomparison Project 6 (CMIP6), both as part of the UK Earth System Model and as a stand‐alone coupled climate model. Plain Language Summary In this article, a new version of the climate model currently used in the United Kingdom (HadGEM3) is presented and analyzed. The circulation of the atmosphere and the oceans is simulated on a relatively coarse spatial grid with a grid cell size of about 120 km. The advantage of using a coarse spatial grid is that less computing power (on a supercomputer) is needed compared to using a finer grid. This gives an opportunity to do many more simulations of the ways in which Earth's climate may evolve in the decades and centuries ahead. We have carefully compared a simulation of the climate around the year 2000 with climate observations from that time and with a simulation from the same model with a finer spatial grid. Our results show that our new, coarse‐grid version is representing the current climate reasonably well, for instance, with regards to climate variability in the tropics and major ocean currents. However, there are clear differences between the two models. In the coarse‐grid model, the ocean surface is too cold in the northwest Atlantic, while in the fine‐grid version it is too warm in the Southern Ocean around Antarctica. We look into explanations for these inaccuracies. Key Points A low‐resolution, traceable version of the current Met Office Hadley Centre climate model HadGEM3 GC3.1 is presented The scientific performance is comparable to the medium‐resolution version, while requiring much less computational resources In the low‐resolution version the Southern Ocean warm bias is reduced, linked with a more realistic ocean circulation

An influence of solar irradiance variations on Earth’s surface climate has been repeatedly suggested. Simulations with a climate model driven by satellite measurements of solar ultraviolet irradiance show an atmospheric response to the solar minimum that resembles the negative phase of the North Atlantic Oscillation. An influence of solar irradiance variations on Earth’s surface climate has been repeatedly suggested, based on correlations between solar variability and meteorological variables 1 . Specifically, weaker westerly winds have been observed in winters with a less active sun, for example at the minimum phase of the 11-year sunspot cycle 2 , 3 , 4 . With some possible exceptions 5 , 6 , it has proved difficult for climate models to consistently reproduce this signal 7 , 8 . Spectral Irradiance Monitor satellite measurements indicate that variations in solar ultraviolet irradiance may be larger than previously thought 9 . Here we drive an ocean–atmosphere climate model with ultraviolet irradiance variations based on these observations. We find that the model responds to the solar minimum with patterns in surface pressure and temperature that resemble the negative phase of the North Atlantic or Arctic Oscillation, of similar magnitude to observations. In our model, the anomalies descend through the depth of the extratropical winter atmosphere. If the updated measurements of solar ultraviolet irradiance are correct, low solar activity, as observed during recent years, drives cold winters in northern Europe and the United States, and mild winters over southern Europe and Canada, with little direct change in globally averaged temperature. Given the quasiregularity of the 11-year solar cycle, our findings may help improve decadal climate predictions for highly populated extratropical regions.

Interannual forecasts provide skilful predictions of El Niño-Southern oscillation (ENSO) up to a year in advance, however our understanding of what drives the ensemble skill and diversity of outcomes across members is limited. Using a fully coupled ocean–atmosphere ensemble forecasting system, we investigate the causality of regional perturbations on the evolution of ENSO at interannual timescales. Using forecasts initialised on 1 November 2009, transplanting more realistic cooler conditions in the South Pacific across ensemble members on 1 January 2010 significantly cools the resulting 2010/2011 winter ENSO one year later. The imposed perturbations migrate equatorward via wind–evaporation–sea surface temperature feedback and significantly alter tropical zonal gradients during late spring and summer. This drives the ensemble towards La Niña conditions, in line with observations. Repeating the experiment with warmer South Pacific conditions, results in the reverse signal and warms ENSO one year later. Across the experiments we find an almost four-fold increase in probability of La Niña and a three-fold decrease in probability of El Niño, demonstrating that long lead regional perturbations can systematically tip the climate system between ENSO states. Predicted surface conditions are significantly impacted across many parts of the world and the forecast global annual mean surface temperature for 2010 is significantly cooled, resulting in better agreement with observations. Our results demonstrate sensitivity of ENSO evolution and the global climate system to specific regional perturbations and provide new insights for interannual climate prediction.

Global mean near surface temperature change is the key metric by which our warming climate is monitored and for which international climate policy is set. At the end of each year the Met Office issues a global mean temperature forecast for the coming year. Following on from the new record in 2023, we predict that 2024 will likely (76% chance) be a new record year with a 1‐in‐3 chance of exceeding 1.5°C above pre‐industrial. Whilst a one‐year temporary exceedance of 1.5°C would not constitute a breach of the Paris Agreement target, our forecast highlights how close we are now to this. Our 2024 forecast is primarily driven by the strong warming trend of +0.2°C/decade (1981–2023) and secondly by the lagged warming effect of a strong tropical Pacific El Niño event. We highlight that 2023 itself was significantly warmer than the Met Office DePreSys3 forecast, with much of this additional observed warming coming from the southern hemisphere, the cause of which requires further understanding. Predictions of global mean surface temperature for 2024 are made showing for the first time a significant chance of exceeding 1.5°C above pre‐industrial. Whilst a one‐year temporary exceedance of 1.5°C would not be a breach of the Paris Agreement target, our forecast highlights how close we are now to this. This further motivates efforts to rapidly transition to net zero global emissions of greenhouse gases and to undertake research to better understand the recent jump in global temperature.

The El Niño-Southern Oscillation (ENSO) events of recent decades have been divided into the two different types based on their spatial patterns, the Eastern Pacific (EP) type and Central Pacific (CP) type. Their most significant difference is the distinguished zonal center locations of sea surface temperature (SST) anomalies in the equatorial Pacific. In this study, based on six operational climate models, we evaluate predictability of the two types of ENSO events in winter to examine whether dynamical predictions can distinguish between the two spatial patterns at lead time of 1 month and tell us more than simply whether an event is on the way. We show that winter EP and CP El Niño and La Niña events can only be distinguished in a minority of these models at 1-month lead, and the EP type tends to has a more realistic zonal positions of SST pattern centers than the CP type. Compared to the SST patterns, the differences between the two types are less apparent in precipitation especially for the two La Niña types in the models. Examinations of the extratropical teleconnections to the two ENSO types show that some of the models can reproduce the differences between EP and CP teleconnections. Evaluations of model predictions show that the EP El Niño event has the same level hit rate with the CP El Niño and the CP La Niña event has much higher hit rate than the EP La Niña. While the multi-model ensemble increases Niño index prediction skill, it does not help to improve forecast skill of center longitude index of the SST patterns and distinguish the two types of ENSO events. Although ENSO skill is very high at this lead time, the rapid loss of the initialized information on the different ENSO types in most of the models severely limits the predictability of the two types of winter ENSO events and more research is needed to improve the performance of climate models in forecasting the two ENSO types.

Climate prediction skill on the interannual timescale, which sits between that of seasonal and decadal, is investigated using large ensembles from the Met Office and CESM initialised coupled prediction systems. A key goal is to determine what can be skillfully predicted about the coming year when combining these two ensembles together. Annual surface temperature predictions show good skill at both global and regional scales, but skill diminishes when the trend associated with global warming is removed. Skill for the extended boreal summer (months 7-11) and winter (months 12-16) seasons are examined, focusing on circulation and rainfall predictions. Skill in predicting rainfall in tropical monsoon regions is found to be significant for the majority of regions examined. Skill increases for all regions when active ENSO seasons are forecast. There is some regional skill for predicting extratropical circulation, but predictive signals appear to be spuriously weak.

Any reduction in global mean near-surface temperature due to a future decline in solar activity is likely to be a small fraction of projected anthropogenic warming. However, variability in ultraviolet solar irradiance is linked to modulation of the Arctic and North Atlantic Oscillations, suggesting the potential for larger regional surface climate effects. Here, we explore possible impacts through two experiments designed to bracket uncertainty in ultraviolet irradiance in a scenario in which future solar activity decreases to Maunder Minimum-like conditions by 2050. Both experiments show regional structure in the wintertime response, resembling the North Atlantic Oscillation, with enhanced relative cooling over northern Eurasia and the eastern United States. For a high-end decline in solar ultraviolet irradiance, the impact on winter northern European surface temperatures over the late twenty-first century could be a significant fraction of the difference in climate change between plausible AR5 scenarios of greenhouse gas concentrations. Regional surface climate response to a future decline in solar activity remains uncertain. Here, via numerical simulations, the authors show that a return to Maunder Minimum-like lows by 2050 could lead to some areas of significantly reduced surface warming via modulation of the North Atlantic Oscillation.